Haiyang Cao

Precise electrical parameter identification is becoming an essential technology in transportation electrification due to the increasing demands for fault diagnosis and online monitoring. However, in the permanent magnet synchronous machine (PMSM), multiparameter identification encounters significant challenges due to the dead-time effect (DTE) resulting from voltage source inverter (VSI) nonlinearity and the degraded signal-to-noise ratio under low-speed conditions. To address this issue, this paper proposes a method that integrates an observation loop and a compensation loop to identify the DTE-induced distortion voltage. By coordinating high-frequency (HF) small-signal injection with the dual extended Kalman filter (DEKF), simultaneous multiparameter identification is achieved. Compared to traditional methods, the proposed method eliminates reliance on precise device parameters or polarity detection, avoids introducing additional delay, and exhibits superior steady-state and transient performance. Notably, it achieves reliable identification even at zero speed and zero load with all parameter initial values set to zero. Furthermore, the design procedure and implementation flowchart of the proposed method are systematically analyzed. Finally, experimental results comprehensively validate its effectiveness under various critical operating conditions.

To suppress position estimation errors inherent in speed-sensorless PMSM control, a frequency-domain shaped nonlinear layered observer is proposed in this brief. The proposed method leverages a smooth gating function to naturally establish a layered mechanism: the outer layer exploits high-order nonlinearity to accelerate back electromotive force convergence, while the inner layer transitions into a linear kernel integrated with an internal model term. Through precise frequency-domain shaping, the observer guarantees zero phase lag and unity gain in BEMF estimation, alongside robust DC-bias suppression. Unlike existing linear or nonlinear methods, the FSNLO simultaneously achieves superior dynamic response and uncompromised frequency-domain shaping capabilities. Rigorous stability analyses prove uniform ultimate boundedness. Comparative experiments validate the superiority of the proposed method, demonstrating remarkable enhancements in both steady-state and dynamic estimation precision.

In ultra-local-model-based finite-control-set model-free predictive current control (FCS-MFPCC) of permanent magnet synchronous motors (PMSMs), the scaling factor critically affects current prediction accuracy, while its conventional fixed design remains sensitive to inductance mismatch. To address this issue, an improved finite control set modelfree predictive current control (FCS-MFPCC) with identification and adaptive switching system to online identify and apply the accurate scaling factor is proposed. First, the influence of scaling-factor deviation on current-variation estimation is analyzed in terms of z-domain pole-zero distribution and maximum estimation error. Then, instead of relying on lumped-disturbance observation under a fixed scaling factor, a unified framework integrating disturbance estimation and input-gain adaptation is developed. A dynamic mapping from the adaptive scaling factor to the estimated lumped disturbance is established, based on which a gain regulation law and an adaptive switching strategy are designed. Finally, the estimated lumped disturbance and updated scaling factor are used to synchronously generate the current increments of all eight candidate switching states for look-up table (LUT) refreshing, while a two-step prediction scheme is adopted to compensate for digital delay. Simulation and experimental results verify improved current tracking performance, lower total harmonic distortions (THD), and enhanced robustness against parameter mismatch.

Deadbeat predictive current control (DPCC) exhibits excellent dynamic performance but is highly sensitive to parameter mismatch, while incremental DPCC (IDPCC) eliminates flux influence yet suffers from poor inductance mismatch tolerance, leading to potential instability. To address these issues, an enhanced DPCC strategy is proposed for permanent magnet synchronous motor (PMSM) drives. First, an incremental extended state observer (IESO) is designed to improve IDPCC’s tolerance to inductance mismatch while offering stronger disturbance estimation capability under the same bandwidth. Second, the enhanced DPCC structure eliminates the dependence on resistance and flux. Third, an inductance self-correcting mechanism based on incremental current deviation is introduced to eliminate the need for accurate prior inductance information and prevent inductance drift during operation. Experiments demonstrate that the proposed method effectively eliminates the influence of flux and resistance mismatch in the system. Even under significant inductance mismatch, it achieves high-precision current tracking with effectively reduced harmonic content, along with improved steady-state performance and faster dynamic response compared to existing DPCC-based methods.

To enhance the control performance of surface-mount permanent magnet synchronous motor (SPMSM) under low switching-to-fundamental frequency ratios (SFRs), an improved discrete-time current regulator (IDCR) is proposed in this brief. The regulator naturally aligns with digital implementation, effectively avoiding performance degradation due to discretization. The designed feedback controller allows arbitrary placement of system poles and eliminates speed-dependent phase terms, ensuring a constant critically damped characteristic. Furthermore, the IDCR achieves precise orthogonal decoupling and, separately, does not require complex predictive computation. The proposed method significantly improves current control performance under low SFRs conditions, and experimental results further verify its effectiveness and superiority.

This paper proposes a novel sensorless control strategy for permanent magnet synchronous motor (PMSM) based on complex coefficient filter-based fixed-time extended state observer (CCF-FESO) and novel cost function-based finite-position- set phase-locked loop (NCF-PLL). Firstly, the CCF-FESO is proposed by integrating a complex coefficient filter (CCF) with a fixed-time convergent extended state observer (FESO). This novel approach overcomes the inherent phase lag and poor sinusoidal tracking performance of conventional linear ESO, enabling accurate estimation of back electromotive force (BEMF). Secondly, the NCF-PLL is designed based on a novel Newton-iteration cost function, which removes the dependency on auxiliary algorithms, thereby simplifying the computational structure while enhancing theoretical precision. Finally, experimental results demonstrate that the proposed strategy achieves a significant improvement in estimation performance, reducing the steady-state position root mean square error (RMSE) by approximately 15.8% and decreasing the maximum dynamic error from 13.1° to below 4.2°, thereby confirming its feasibility and superiority.

Under complex operating conditions, deadbeat predictive current control (DPCC) is susceptible to multisource disturbances, including periodic and aperiodic components, which degrade the current control accuracy. To address this issue, a DPCC strategy based on a complex vector disturbance observer (CVDO) is proposed for the current loop of permanent magnet synchronous motor (PMSM) drives. First, the structure of the CVDO is developed from the PMSM mathematical model, and its sensitivity function is derived. On this basis, the CVDO is designed in the frequency domain to achieve precise estimation of multisource disturbances. Distinct from existing observers with embedded resonant structures, the proposed CVDO is designed directly from the perspective of frequency-domain response. This approach achieves ideal frequency-domain characteristics and facilitates stability analysis. Benefiting from a unique multiband synergistic architecture, the proposed method not only achieves the accurate separation and extraction of positive- and negative-sequence harmonics as well as aperiodic disturbances, but also effectively overcomes the disturbance amplification problem inherent in existing methods. Significantly, this architecture allows for the independent adjustment of disturbance estimation across different frequency bands, thereby enabling the independent optimization of observation performance for each band. Thus, this enhances the degrees of freedom in parameter tuning and improves design flexibility. Furthermore, the estimation performance and stability of the observer are analyzed theoretically. Finally, the effectiveness and advantages of the proposed method are validated on a PMSM platform.

When suppressing both aperiodic and periodic disturbances in surface-mounted permanent magnet synchronous motor (SPMSM), the traditional method based on a two-degree-of-freedom (TDOF) parallel quasi-resonant controller suffers from inherent coupling issues. These include coupling between tracking and anti-disturbance performance, as well as coupling between the aperiodic and periodic disturbance suppression loops. To address these issues, a novel TDOF structure is proposed based on the SPMSM discrete-time complex vector model, incorporating an enhanced resonant controller. This design effectively eliminates undesired peaks caused by coupling without requiring complex parameter tuning. Theoretical analysis shows that the proposed method achieves improved stability, enhanced aperiodic and periodic disturbance suppression performance, and greater robustness to parameter mismatches. Experimental results further validate the effectiveness of the approach in all these aspects.